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Statistical Monitoring Techniques for Contamination Data

机译:污染数据的统计监测技术

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Monitoring of particle contamination by statistically based methods is used extensively in semiconductor manufacturing. Often Shewhart-type control charts are used for this purpose. These charts suffer from some potential disadvantages in this application environment. Specifically, they are slow to detect shifts or changes in the level of particle contamination and, in some situations, the underlying statistical assumptions of the charts are inappropriate for contamination data. We suggest the use of cumulative sum and exponentially weighted moving average control charts for monitoring particle contamination. The advantages of these charts for the types of particle contamination data typically encountered in semiconductor manufacturing are discussed and illustrated with examples. particle contamination; cumulative sum (CUSUM); exponentially weighted moving average (EWMA); statistical monitoring
机译:通过基于统计的方法来监视颗粒污染已广泛用于半导体制造中。通常,Shewhart型控制图用于此目的。这些图表在此应用程序环境中存在一些潜在的缺点。具体而言,它们检测颗粒污染水平变化或变化的速度很慢,并且在某些情况下,图表的基础统计假设不适用于污染数据。我们建议使用累积总和和指数加权移动平均值控制图来监视颗粒污染。讨论并举例说明了这些图表对于半导体制造中通常遇到的颗粒污染数据类型的优势。颗粒污染;累计金额(CUSUM);指数加权移动平均线(EWMA);统计监测

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